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Shock result as Rodez defy the odds to beat Annecy 2-1.

📝 Match Report

How It Unfolded

Rodez beat Annecy 2-1 at Stade Paul-Lignon, Regular Season - 12, in the Ligue 2. With the result on the board, the sections below measure it against everything the model and the numbers projected in advance.

The Model vs The Result

The Poisson model went into this projecting Rodez 1.08 xG and Annecy 1.19 xG, a combined 2.27. The scoreboard read 2-1 for 3 actual goals. Rodez beat their projection by 0.9 — clinical relative to the chances the model priced in. Those figures were built on strength ratings of Rodez attack 0.88 / defence 1.01 against Annecy attack 0.96 / defence 1.00, drawn from 45/45 games (CurrentSeason).

On the result, the model split it Rodez 33% | Draw 29% | Annecy 39%, with Annecy to win its most likely call at 39%. The actual Rodez win had been the model's second-ranked read at 33%, so the result diverged from the top call without being a shock.

Goals & Markets

The model rated Over 2.5 goals at 40%. The game delivered 3, so it went over — the opposite of the projected direction. Over 1.5 had been 66% and landed. On both teams to score, the model sat at 46% and the match saw both sides score — a miss on BTTS. Historically the two sides average 48% Over 2.5 across their same-competition games (Rodez 58%, Annecy 38%), a base rate that pointed the other way from today's over. Their combined BTTS history runs at 54%, which matched the both-scored outcome.

Trading Patterns vs Reality

Rodez's trading profile (45 games, 23 home) set some clear expectations: BTTS lands in 67% of their matches — today it did.

Annecy's trading profile (45 games, 23 away) set some clear expectations: BTTS lands in 42% of their matches — today it did; they keep a clean sheet 44% of the time, and conceded here.

Form vs Result

The form lines were close — Rodez 1.16 PPG, Annecy 1.47 PPG — offering no strong steer, and the Rodez win broke the near-deadlock.

Verdict

Grading the result against the stored data, 0 of 3 pre-match signals came in: result (miss), Over 2.5 (miss), BTTS (miss). The data was on the wrong side of this result more often than not — a reminder that a single match sits well inside the model's variance.

💡 Key Insights